Economy as a Social Institution in the Tribal Society: A Scale to Measure the Perceived Role Performance of Economic Institutions

Abstract

Economic institutions play a pivotal role in achieving sustainable development goals (SDGs) among tribal communities. Despite improved access to economic institutions and their services through government and private interventions, a majority of tribals in India continue to face extreme poverty. This study focuses on developing and validating a scale to measure the perceived role performance of economic institutions in tribal societies. Employing Likert’s summated rating scale construction technique, a scale comprising 10 statements related to economic institutions’ roles has been developed. Standardisation through reliability and validity measures, as well as confirmatory factor analysis (CFA), confirms the robustness of the scale. Administered to 270 tribal respondents in Salem, Tiruvannamalai and Viluppuram Districts of Tamil Nadu, our findings unveil diverse roles and challenges faced by economic institutions in tribal societies. The study reveals a nuanced perception among tribal respondents, with a majority indicating a medium to high level of perception. However, a notable proportion demonstrates a low perception level, highlighting areas of concern. The study underscores the importance of targeted strategies to boost financial inclusion and empower tribal communities. It also provides policy recommendations for addressing challenges and fostering sustainable development within tribal societies.

Keywords

Scheduled tribe banks cooperative society Summated Rating Scale Construction Perception CFA

Introduction

This study focuses on tribal economic institutions, attempting to examine how economic institutions function in tribal societies and the way tribal communities perceive these institutions to function in their respective capacities. In today’s diverse world, over 476 million indigenous people from more than 5,000 civilisations inhabit 90 countries, accounting for about 6.20% of the global population (United Nations 2021a). These communities, spread across continents, are crucial to the development of our society. Despite their rich cultural heritage, over one-third of indigenous people face the harsh reality of extreme poverty, accounting for more than 15% of all extremely poor people globally, raising concerns about their well-being (Mamo 2020).

India has the second-highest population of global tribal population. According to Article 366 (25) of the Constitution, indigenous people in India are referred to as scheduled tribes (STs). In India, 30 states/UTs have designated a total of 705 distinct ethnic groups as STs. There are 104.3 million tribal people in India, accounting for 8.60% of the country’s total population (Census 2011). The STs are India’s poorest people, with five out of ten living in poverty. Overall, 40.60% of the ST population was poor, compared to 20.50% of the non-tribal population. Despite only 8.00% of the population of the country, 45.90% of STs are impoverished, compared to 26.60% of SCs, 18.30% of other backward classes (OBCs), 9.70% of other castes and 25.30% of those whose caste is unknown (International Institute for Population Sciences (IIPS) and ICF 2017).

Addressing the challenges confronting tribal populations necessitates targeted strategies, particularly in the realms of financial services and economic institutions. In this pursuit, economic institutions serve as key agents in realizing important sustainable development goals (SDGs), such as decent work and growth in the economy, which, in turn, have far-reaching impacts on poverty alleviation, health, education, gender equality and sanitation. In India, a multitude of government schemes have been implemented to uplift the socio-economic situation of tribal communities. The proliferation of economic institutions, including public and private banks, as well as cooperative societies, has increased in tribal areas over the years, attempting to bridge the prevailing gaps.

Despite numerous government initiatives and an increased presence of economic institutions in tribal areas, socio-economic disparities persist, and a considerable portion of the ST population continues to live in poverty. The United Nations has emphasised the need for developing nations to adopt suitable measures for enhancing the accessibility of financial services, particularly for underprivileged people (United Nations 2021b). By understanding the roles and functions of economic institutions, especially in the context of tribal societies, we can unlock pathways to sustainable development, financial inclusion and improved livelihoods. Measuring the performance of economic institutions in tribal communities is challenging. This study aims to create a psychometric scale to assess the perceived role performance of these institutions among tribal communities.

Review of Literature

In tribal societies, economic institutions play a vital role in meeting fundamental needs like food, shelter and clothing. They contribute to the well-being of tribal communities by providing financial assistance and employment opportunities, especially evident through government initiatives aimed at enhancing the socio-economic status of STs. There has been a noticeable increase in economic institutions in tribal areas, such as public and private banks and Large Area Multipurpose Societies (LAMPS).

The research conducted by Gandhi and Marsh (2003) delved into the interplay between local institutions, both formal and informal, and economic development. This exploration unveiled the substantial contribution of local institutions, ranging from service cooperatives to saving groups, in enhancing household incomes and capital assets, thereby bolstering socio-economic well-being over time. Further illumination emerges from Gowda’s (2003) comprehensive investigation of tribal cooperatives, emphasising the potential of LAMPS to bolster tribal welfare while fostering substantial profits.

Akoijam (2013) emphasises the pivotal role of rural credit as a lifeline for India’s rural population without alternative income sources, with delivery facilitated by organisations such as Regional Rural Banks (RRBs), microfinance institutions and National Bank for Agriculture and Rural Development (NABARD). Deepening the exploration, Kumar’s (2017) study documented tribal reliance on informal credit sources such as moneylenders, friends and relatives. In parallel, Kannan’s (2013) research on the tribes of Tamil Nadu shed light on LAMPS’ multifaceted roles, encompassing agricultural loans, protection against exploitation by moneylenders and the sustenance of tribal economies through marketing of the minor forest products.

Usharani’s (2017) in-depth analysis examined the functioning of LAMPS in tribal areas in Karnataka, acknowledging their services while highlighting nuanced challenges driven by tribal demographics and life patterns. In the broader context, the literature emphasises the pivotal role of economic institutions in uplifting tribal well-being, recognising their significance in employment and financial avenues. However, persistent challenges call for a thorough understanding of the intricate relationships between economic institutions and SDGs, emphasising the need for a comprehensive scale to measure the contribution of economic institutions to the overall well-being of tribal communities.

This study draws from and expands upon previous literature to establish a robust theoretical basis for comprehending the functions of economic institutions within tribal communities. The scale that is envisioned aims to provide insightful information about how well economic institutions performed their roles to promote sustainable development and address socio-economic disparities within tribal communities. In this pursuit, this study aims to empower tribal populations and align with the aspirations of the SDGs of the United Nations.

Research Methodology

Sampling Procedure

This study was carried out in Tamil Nadu, a state in India known for its rich cultural diversity and tribal presence. To ensure robust representation and insightful findings, the sample selection process was carefully planned out, taking into account different levels, including districts, blocks, villages and individual respondents. The study focused on three strategically chosen districts: Salem, Tiruvannamalai and Viluppuram, employing a purposive sampling method to target tribal-dominated districts.

The rationale behind the choice to select these districts was firmly grounded in several levels of justification, creating a solid base for the research design. First, empirical analysis of the 2011 Census data identified them as the top three districts in Tamil Nadu concerning the STs population. Second, strategically located in the Eastern Ghats, these districts significantly influence the socio-cultural fabric and livelihood patterns of tribal communities. Additionally, the declaration of ‘scheduled areas’ under the Integrated Tribal Development Programme (ITDP) in these districts underscores their unique challenges, reinforcing the study’s focal point.

The sample selection was enhanced by identifying specific blocks within each district based on STs’ population density. Pethanaickenpalayam, Jawadhu Hills and Kalrayan Hills blocks were chosen using purposive sampling. Additionally, three villages were purposively selected from each block based on the highest tribal population, which resulted in a total of nine villages. Subsequently, individual respondents were selected from different households in the nine villages. Therefore, considering the population size as the total number of households (831) in the nine villages, the appropriate sample size for the study was determined by applying Yamane’s formula (Yamane 1967), expressed as follows:

n = \frac{N}{1 + N e^{2}}

Where,

n is the sample size.

N is the population size (number of households).

e is the error tolerance.

With a population size (N) of 831 and an error tolerance (e) set at 0.05 (indicating a 95% confidence interval), the formula yielded a calculated sample size (n) of 269.64, rounded to 270 for practical implementation. To ensure balanced representation, 90 STs respondents were deliberately chosen from each district. A proportionate random sampling technique was employed for each district to determine the number of sample respondents within each village, treating the three villages within each district as distinct strata.

The formula used for the proportionate random sampling method is expressed as follows:

n_{i} = \frac{N_{i}}{N} \times n

Where,

n_i is the number of tribal households to be selected from the ith village within the district.

N_i is the number of tribal households in the ith village within the district.

N is the total number of tribal households in the three villages within the district.

n is the total number of tribal households to be selected from the three villages within the district.

Based on the formula, the number of samples from each village was finalised and presented in Table 1, which displays the sampling frame. This sampling approach adheres to the principles of both purposive and probability sampling, combining the advantages of targeted representation with statistical validity.

Table 1.

Sampling Framework of the Study.

S.No.	District	Block	Villages	Tribal Households in the Village	No. of Tribal Households Selected from the Village
1.	Salem	Pethanaicken-palayam	Soolankurichi	137	40
			Adiyanur	99	29
			Pudhu-pappanaickenpatty	72	21
			Subtotal	308	90
2.	Tiruvannamalai	Jawadhu Hills	Jamunamarathur	114	39
			Alanjanur	82	28
			Pakkumudaiyanur	67	23
			Subtotal	263	90
3.	Viluppuram	Kalrayan Hills	Chinnapalapoondi	92	32
			Pacheri	90	31
			Serappattu	78	27
			Subtotal	260	90
Total				831	270

Source: Project Officer, Tribal Welfare Office, Salem, Tiruvannamalai and Viluppuram districts.

Scale Development Procedure

The scale was developed by using Likert’s summated rating scale construction method, chosen for its simplicity compared to other methods. This method consisted series of steps, that is, generating a sample of items, relevancy test, item analysis, the final selection of items and standardisation of the scale (Figure 1).

Figure 1.

Steps involved in the Likert’s Summated Rating Scale Construction.

Step I: Generating a sample of items

In the initial phase of scale development, items reflecting the perceived role performance of economic institutions were formulated. This involved a literature survey, consultations with experts in extension education and sociology, discussions with researchers and extension functionaries working with tribal communities and a pilot survey exploring the roles of economic institutions in tribal society. Fifty statements were initially generated and then edited following Likert (1932) and Edwards (1957) standards, resulting in the retention of 35 statements. The selected statements encompass both positive and negative aspects to represent the role performance of economic institutions.

Step 2: Relevancy test

A relevancy test was carried out by using a Google form created with 35 statements. The form was sent to 55 judges who specialised in extension education and sociology research in State Agricultural University (SAUs), and Indian Council of Agricultural Research (ICAR) institutions dealing with tribal studies. The experts were asked to rate them based on their relevancy under a five-point response scale, that is, most relevant, relevant, somewhat relevant, least relevant and not at all relevant with respective scores of 5, 4, 3, 2 and 1. After 2 months, 30 judges (n₁) recorded their responses. With the judges’ responses, the relevancy weightage (RW) and mean relevancy score (MRS) for the statements were calculated by following the formula:

Relevancy weightage (RW) = \frac{Actual score obtained for the statement}{Maximum possible score}

Mean relevancy score (MRS) = \frac{Actual score obtained for the statement}{Number of judges}

The statements with an RW value exceeding 0.75 and an MRS value surpassing 3.25 have been chosen for further analysis. Consequently, 20 statements were finalised for item analysis and are shown in Table 2.

Table 2.

List of Statements with their Relevancy Weightage (RW), Mean Relevancy Score (MRS) and t-Value.

S. No.	Functions of Economy	Relevancy Test (n₁ = 30)		Item Analysis (n₂ = 80)	Selection
S. No.	Functions of Economy	RW	MRS	t-Value	Selection
1.	Nationalised banks help the tribes in aggregating their meagre savings through SHGs	0.76	3.78	3.525	Selected
2.	Cooperative societies adds value to the self-respect of tribes in the society	0.77	3.84	1.461	Rejected
3.	Cooperative banks distribute interest-free crop loans to small-scale tribal farmers	0.75	3.74	2.769	Selected
4.	Banks ensure the production and distribution of goods and services in society	0.79	3.94	1.627	Rejected
5.	LAMPS provide marketing facilities for the sale of agricultural produce	0.84	4.18	3.591	Selected
6.	Banks are not essential for the formation and sustenance of society*	0.82	4.12	1.053	Rejected
7.	LAMPS provide all inputs like seeds, fertilisers and pesticides to the tribal farmers at subsidised prices	0.80	3.98	4.146	Selected
8.	Banks empower tribes to meet their material needs	0.76	3.78	-0.526	Rejected
9.	Nationalised banks does not assist tribes in starting a new business*	0.78	3.90	5.657	Selected
10.	Banks do not create good conditions for entrepreneurship	0.77	3.84	–0.980	Rejected
11.	Banks helping tribes to get out from clutches of moneylenders	0.84	4.18	3.918	Selected
12.	Banks satisfy the economic and bio-social needs of society	0.79	3.96	0.535	Rejected
13.	Cooperative societies create new job opportunities for members in the tribal society	0.76	3.80	0.249	Rejected
14.	Banks in tribal areas do not provide access to affordable insurance services*	0.82	4.08	3.597	Selected
15.	Nationalised banks help in Direct Benefit Transfer of the monetary benefits of welfare	0.76	3.82	–1.635	Rejected
16.	Banks financially empowering women through SHG-based entrepreneurship	0.81	4.04	4.208	Selected
17.	Cooperative banks fail to adapt to the changing needs of tribal society*	0.82	4.12	0.590	Rejected
18.	LAMPS generate employment opportunities for tribes in collecting and marketing minor forest products	0.76	3.80	2.181	Selected
19.	Commercial banks make tribal people become more indebtedness*	0.76	3.80	2.640	Selected
20.	Cooperative banks help business in the tribal society to earn more money	0.80	4.02	1.579	Rejected

Source: Judges opinion and field survey (2019–20).

Notes: *—negative statement; n₁—number of judges in the relevancy test; n₂—number of respondents in item analysis. LAMPS; Large Area Multipurpose Societies; SHGs, self-help groups.

Step 3: Item analysis

In Likert’s summated rating scale creation, item analysis is pivotal for identifying internally consistent items by removing inconsistent ones (Spector 1992). The 20 items were administered to 80 randomly selected tribal respondents through personal interviews, using a five-point scale. Positive statements received scores from 5 to 1, while negative statements received opposite scores. Respondents were ranked by overall score, and the top and bottom 25% formed high and low groups, respectively, serving as criterion groups.

Critical ratios (t-values) for each statement, indicating how well it distinguished between the groups, were determined based on Edwards’ (1957) formula.

t = \frac{{\bar{X}}_{H} - {\bar{X}}_{L}}{\sqrt{\frac{S_{H}^{2}}{n_{H}} + \frac{S_{L}^{2}}{n_{L}}}}

Where,

X̅_H is the mean score on a given statement for the high group.

X̅_L is the mean score on the same statement for the low group.

$S_{H}^{2}$ is the variance of the distribution of responses of the high group to the statement.

$S_{H}^{2}$ is the variance of the distribution of responses of the low group to the statement.

n_H is the number of individuals in the high group.

n_L is the number of individuals in the low group.

Step 4: Final selection of items

Finally, the items having a t-value more than and equal to 1.75 were selected for inclusion in the desired scale. In this manner, 10 statements were finalised. The critical ratios (t-values) of the selected items were given in Table 2 along with their RW and MRS obtained from the relevancy test.

Step 5: Standardisation of the scale

The scale was standardised by assessing its reliability using Cronbach’s alpha and determining validity through the content validity of the items.

Reliability of the Scale

Cronbach’s alpha was used to assess reliability, a widely employed method for gauging the internal consistency of a scale. Conceptually, α is the mean of all potential split-half correlations within a set of items and is influenced by the total number of items and their average inter-correlation (Cronbach, 1951). The formula for Cronbach’s alpha is as follows:

α = \frac{N \bar{c}}{\bar{v} + (N - 1) \bar{c}}

Where,

N is the number of items.

$\bar{c}$ is the average inter-item covariance among the items.

$\bar{v}$ is the average variance.

The 10 statements were administered to 50 tribal respondents from the non-sample area. The collected data were tabulated and analysed for internal consistency using SPSS software. The scale’s Cronbach’s alpha (r) was 0.782. An acceptable measure of internal consistency may be a 0.70 or higher value of Cronbach’s alpha (Santos 1999; DeVellis, 2011). As a result, the scale produced is reliable because the reliability coefficient (0.782) was higher than 0.70. The Cronbach’s alpha if the item deleted values of all the statements were lower than the scale’s overall Cronbach’s alpha value. So, we can retain all 10 statements in the scale (Table 3).

Table 3.

List of Statements with Cronbach’s Alpha of the Scale.

S. No.	Items	Corrected Item-Total Correlation	Cronbach’s Alpha if Item Deleted
1.	Nationalised banks help the tribes in aggregating their meagre savings through SHGs	0.385	0.771
2.	Cooperative banks distribute interest-free crop loans to small-scale tribal farmers	0.323	0.779
3.	LAMPS provide marketing facilities for the sale of agricultural produce	0.514	0.755
4.	LAMPS provide all inputs like seeds, fertilisers and pesticides to the tribal farmers at subsidised prices	0.548	0.750
5.	Nationalised banks does not assist tribes in starting a new business*	0.630	0.736
6	Banks helping tribes to get out from clutches of moneylenders	0.724	0.721
7	Banks in tribal areas do not provide access to affordable insurance services*	0.351	0.774
8	Banks financially empowering women through SHG-based entrepreneurship	0.544	0.751
9	LAMPS generate employment opportunities for tribes in collecting and marketing minor forest products	0.103	0.797
10	Commercial banks make tribal people become more indebted*	0.305	0.780

Source: Field Survey (2020).

Note: *—negative statement; LAMPS, Large Area Multipurpose Societies; SHGs, self-help groups.

Validity of the Scale

The scale has been evaluated on content validity, a critical aspect in the creation of any new measurement tool. Content validity serves as a pivotal indicator of an instrument’s validity by gauging how effectively the instrument measures the intended construct it was designed to assess (Anastasi 1985).

To establish content validity, a panel of experts evaluated the 10 items. These experts were requested to assess the degree to which the items covered various roles and functions of economic institutions. They provided their judgments on a four-point scale of ‘most adequately covered’ (scored as 4), ‘more adequately covered’ (scored as 3), ‘less adequately covered’ (scored as 2) and ‘least adequately covered’ (scored as 1). A total of 40 judges participated in this process. To determine content validity, a benchmark mean score of 2.5 was set. In this case, the computed overall mean of the scale was 3.69, indicating that the constructed scale is indeed valid.

As a result, the constructed scale is considered to be valid and reliable and can be used for measuring the perceived role performance of economic institutions among the tribal communities.

Step 6: Confirmatory factor analysis (CFA)

The scale comprised 10 statements, with seven being positive and the remaining three negative. The scale was administered to selected respondents, and CFA was conducted to assess how well the generated model fit the data. The model’s fit was evaluated using various indices of absolute fit measures and incremental fit measures, all detailed in Table 4.

Table 4.

Model Fit Summary of Confirmatory Factor Analysis.

S. No.	Indices	Value	Suggested Value
(i)	Chi-square value	86.256	–
(ii)	Degrees of freedom (DF)	35	–
I	Measures of absolute fit
1.	P value	.000	>.05 (Hair et al. 1998)
2.	Chi-square value/DF	2.464	<5.00 (Hair et al. 1998)
3.	Root mean square residual (RMR)	0.011	<0.08 (Hair et al. 2006)
4.	Root mean square error of approximation (RMSEA)	0.074	<0.08 (Hair et al. 2006)
5.	Goodness of fit index (GFI)	0.939	>0.90 (Hu and Bentler 1999)
6.	Adjusted goodness of fit index (AGFI)	0.904	>0.90 (Hair et al. 2006)
II	Measures of incremental fit
1.	Normed fit index (NFI)	0.976	>0.90 (Hu and Bentler 1999)
2.	Relative fit index (RFI)	0.969	>0.90 (Byrne 2010)
3.	Incremental fit index (IFI)	0.985	>0.90 (Byrne 2010)
4.	Tucker–Lewis index (TLI)	0.981	>0.90 (Hu and Bentler 1999)
5.	Comparative fit index (CFI)	0.985	>0.90 (Hooper et al. 2008)

Source: Field Survey (2021).

The extent to which the entire model predicts the observed covariance or correlation matrix is assessed through absolute fit measurements (Hair et al. 2006). The results indicated that the absolute fit measures, including the Chi-square value/degrees of freedom (DF) at 2.464, root mean square residual (RMR) at 0.011, root mean square error of approximation (RMSEA) at 0.074, goodness of fit index (GFI) at 0.939 and adjusted goodness of fit index (AGFI) at 0.904, met the criteria for fit indices.

Incremental fit measures are employed to assess how effectively the given model aligns with the sample data in comparison to some other model that serves as a baseline (Hair et al. 2006; Hooper et al. 2008; Malhotra and Dash 2012). These incremental fit measures, including the normed fit index (NFI) at 0.976, relative fit index (RFI) at 0.969, incremental fit index (IFI) at 0.985, Tucker–Lewis index (TLI) at 0.981 and comparative fit index (CFI) at 0.985, show that the model has an excellent fit to the data. The path diagram for the model with 10 statements is shown in Figure 2.

Figure 2.

Note: *—negative statement; LAMPS, Large Area Multipurpose Societies; SHGs, self-help groups.

It could be inferred based on CFA fit indices and the path diagram that the constructed scale’s proposed model perfectly fits the sample data. This suggests that all the 10 statements included in the scale perfectly measure the construct it intends to measure. Hence, the scale can be used to analyse the perceived role performance of economic institutions among the unprivileged population worldwide.

Administration of the Scale

The responses of tribal respondents were collected through the personal interview method to articulate their perspectives on each statement of the scale through a five-point Likert scale. This scale included options ranging from ‘strongly agree’ to ‘strongly disagree’, with scores of 5, 4, 3, 2, and 1 assigned to indicate varying degrees of agreement or disagreement. Notably, positive statements received higher scores for stronger agreement, while negative statements were scored in reverse.

Stratification Method: Cumulative Square Root of Frequency

To analyse respondents’ overall perceptions, a stratification method called the cumulative square root of frequency (CSRF) was applied. This method, proposed by Raghavarao (1987), offers a systematic way to categorise respondents into distinct groups. The detailed steps involved in applying the CSRF method are outlined below:

Determined number of classes and class interval: The optimal number of classes was determined using a sample size-specific formula, and the class interval was then computed based on the results of the relevant formulas.

Number of classes = 2.5 \times {(Number of samples)}^{1 / 4}

Class interval = \frac{Largest figure - Smallest figure}{Number of classes}

Assigned respondents to classes: Following the determination of classes, respondents were systematically allocated to these classes using the calculated class interval.

Calculated square root of frequency for each class: The square root of the frequency for each class was computed.

Determined cumulative square root frequencies: Cumulative square root frequency for each class is obtained by summing the square root frequencies of all preceding classes.

Calculated cumulative square root (L_i) values: The cumulative square root (L_i) values were calculated by multiplying the cumulative square root frequency of the last class by 1, 2, ..., i and dividing by the desired number of sample strata (one-third and two-thirds in this case) to obtain cumulative square root (L_i) values.

Established strata boundary values: The boundary values of the strata were established by using a designated formula.

L = K + [\frac{L_{i} - C}{\sqrt{f}}] \times n

Where,

K is the lower limit of the class in which L_i lies.

C is the cumulative square root of the frequency of the preceding class in which L_i lies.

n is the interval of the class.

f is the square root of the frequency of the ith class in which L_i lies.

Stratification: Strata were formed based on the calculated boundary values:

Below L1 value: Low

Between L1 and L2 values: Medium

Above L2 values: High

This stratification method provides a nuanced categorisation of respondents into low, medium and high perception levels, offering insights into the diverse perspectives within the tribal communities.

Results and Discussion

This section extensively examines a scale designed to assess the perceived role performance of economic institutions. The 10 statements in the scale delve into the complex economic interactions shaping the lives of tribal communities. Six statements scrutinise the roles of commercial banks, covering financial empowerment, credit access and support for entrepreneurship. The remaining four highlight cooperative societies’ contributions to agriculture, marketing assistance and employment generation. This multifaceted scale not only captures distinct functions but also provides a lens to analyse nuanced impacts on tribal well-being, contributing to discussions on sustainable development and financial inclusion. The results detailed in Table 5 offer intriguing insights into economic institution dynamics within tribal communities, focusing on commercial banks and cooperative societies (LAMPS).

Table 5.

Perception of Tribal Respondents on the Role Performance of Economic Institutions.

S. No.	Functions of Economy	Strongly Agree		Agree		Undecided		Disagree		Strongly Disagree
S. No.	Functions of Economy	f	%	f	%	f	%	f	%	f	%
1.	Nationalised banks help the tribes in aggregating their meagre savings through SHGs	61	22.59	98	36.30	48	17.78	54	20.00	9	3.33
2.	Cooperative banks distribute interest-free crop loans to small-scale tribal farmers	70	25.93	109	40.37	46	17.03	30	11.11	15	5.56
3.	LAMPS provide marketing facilities for the sale of agricultural produce	60	22.22	95	35.19	29	10.74	40	14.81	46	17.04
4.	LAMPS provide all inputs like seeds, fertilisers and pesticides to the tribal farmers at subsidised prices	86	31.85	66	24.44	50	18.52	51	18.89	17	6.30
5.	Nationalised banks does not assist tribes in starting a new business*	69	25.56	73	27.04	52	19.26	46	17.04	30	11.11
6.	Banks helping tribes to get out from clutches of moneylenders	75	27.78	88	32.59	26	9.63	46	17.04	35	12.96
7.	Banks in tribal areas do not provide access to affordable insurance services*	69	25.56	86	31.85	57	21.11	43	15.93	15	5.56
8.	Banks financially empowering women through SHG-based entrepreneurship	31	11.48	35	12.96	64	23.70	72	26.66	68	25.19
9.	LAMPS generate employment opportunities for tribes in collecting and marketing minor forest products	52	19.25	94	34.81	38	14.07	50	18.52	36	13.33
10.	Commercial banks make tribal people become more indebted*	33	12.22	59	21.85	49	18.15	69	25.56	60	22.22

Source: Field Survey (2021).

Note: *—Negative statements/f—frequency. LAMPS, Large Area Multipurpose Societies; SHGs, self-help groups

Commercial Banks

From the findings, it can be observed that among the statements representing the functions of commercial banks, the statement ‘Banks helping tribes to get out from clutches of moneylenders’ obtained agreement by nearly two-thirds (60.37%) of the respondents, which indicates that moneylenders are suppressing the tribes by getting more interest for the loan amount. As indicated by the substantial agreement with the statement, it is clear that commercial banks have been successful in reducing the reliance on local moneylenders, contributing to financial independence. This finding resonates with the observations made by Gandhi and Marsh (2003), indicating the pivotal role of local institutions in enhancing household incomes and capital assets. However, the persistence of disagreement (30.00%) on the statement shows that there is still a sizable of tribes getting money from local moneylenders for urgent needs. This is because it is challenging to obtain quick loans from formal institutions. The persisting disagreement highlights the challenges posed by factors like accessibility, knowledge gaps and illiteracy, as emphasised in previous studies (Kumar 2017; Usharani 2017).

The statement ‘Nationalised banks help the tribes in aggregating their meagre savings through self-help groups’ (SHGs) has gained agreement from more than half (58.89%) of respondents, and only 23.33 per cent of respondents showed disagreement. The positive impact of nationalised banks in supporting savings mobilisation through SHGs echoes the findings of Gowda (2003), emphasising the collaborative efforts between formal financial institutions and community-driven initiatives. This collaboration not only fosters financial resilience but also contributes to the extensive involvement of tribal women in building economic stability.

Slightly over half (51.85%) of the participants expressed their disagreement with the statement that ‘Banks contribute to the financial empowerment of women through SHG-based entrepreneurship’, while about a quarter (24.49%) of the respondents agreed with this statement. While SHGs are prevalent, the absence of a majority consensus suggests a need for a closer examination of how SHG involvement can truly drive entrepreneurship and empowerment. This situation could also be influenced by the entrepreneurial aspirations inherent in tribal communities, particularly among tribal women, intertwining deeply with their cultural values and motivational factors. The divergence in responses underscores the nuanced challenges of aligning financial services with cultural values and individual aspirations, a theme also explored by Usharani (2017).

Regarding the negative statements about the functions of commercial banks, just over half (52.60%) of respondents agreed with the statement ‘Nationalised banks do not assist tribes in starting a new business’, while more than one-fourth (28.15%) of tribal respondents showed disagreement towards the assertion. It highlights the difficulties that tribal members encounter when trying to obtain loans to launch their businesses. This finding is consistent with the complex network of socio-economic factors like lack of self-esteem and self-motivation among the tribes that constrain entrepreneurial opportunities. A total of 57.41 per cent of tribal respondents agreed with the assertion that ‘Banks in tribal areas do not provide access to affordable insurance services’, while 21.49 per cent disagreed with it. Similar to the previous statement, it also emphasises the need to remove any obstacles to accessibility while also recognising the importance of insurance for risk reduction in these situations.

Nearly half (47.78%) of the tribal respondents disagreed with the assertion that ‘Commercial banks make tribal people become more indebted’, while one-third (34.07%) of the respondents agreed with it, revealing divergent viewpoints. Although there is a consensus that banks do not cause indebtedness, the agreement of a sizable minority encourages consideration of the scenarios in which financial services might unintentionally cause indebtedness. This response might have been influenced by factors like a lack of financial literacy, unforeseen financial challenges, cultural values and fear of financial institutions.

Cooperative Societies (LAMPS)

Regarding the roles performed by cooperative societies (LAMPS), the statement ‘Cooperative banks distribute interest-free crop loans to small-scale tribal farmers’ obtained substantial agreement (66.30%) among the tribal respondents, whereas 16.67 per cent of the tribal respondents showed disagreement with this statement. This substantiates the pivotal role played by these societies in facilitating access to credit for tribal farmers. Such a role aligns with their crucial function in supporting agricultural endeavours and assisting small-scale farmers in sustaining their livelihoods.

A sizable majority of respondents (57.41%) agreed with the statement that ‘LAMPS provide marketing facilities for the sale of agricultural produce’, while almost one-third (31.80%) of respondents disagreed on the same. Similarly, over half (56.29%) of the tribal respondents agreed upon the assertion that ‘LAMPS provide all inputs like seeds, fertilisers, and pesticides to the tribal farmers at subsidised prices’, but one-fourth (25.19%) of the respondents disagreed. The widespread agreement on these two statements highlights the comprehensive assistance offered by LAMPS, which boosts agricultural productivity by supplying affordable, high-quality inputs to tribal farmers and promotes economic stability by assisting tribal farmers with marketing. Additionally, it is also important to point out that a significant proportion of negative responses to these two statements may be attributable to the tribal farmers’ lack of land ownership, which prevents tribes from gaining membership and taking advantage of the services provided by cooperative societies.

Furthermore, just over half (54.06%) of the tribal respondents agreed upon the assertion that ‘LAMPS generate employment opportunities for tribes in collecting and marketing minor forest products’. However, nearly one-third (31.85%) of the respondents disagreed. This highlights the potential of cooperative societies not only in meeting economic needs but also in fostering sustainable employment in tribal areas. The substantial agreement on the positive roles played by LAMPS aligns with the emphasis on the potential of LAMPS to bolster the tribal welfare of tribal farmers and enhance profits, as discussed by Gowda (2003) and Kannan (2013). However, the notable level of disagreement on some statements calls attention to barriers preventing tribal communities from fully utilising the services offered by cooperative societies, echoing Usharani’s (2017) insights on the challenges driven by tribal demographics and life patterns.

The examination of individual statement-level analysis unveils intricate details regarding the perceived role performance of economic institutions within tribal societies. Noteworthy findings include the significant role of commercial banks in reducing reliance on local moneylenders and the positive impact of cooperative societies in supporting agricultural endeavours. However, challenges persist, especially in the areas of entrepreneurship empowerment, access to financial services and the utilisation of cooperative functions.

The Overall Perception

To delve deeper into the nuances of tribal respondents’ perceptions, they were categorised into low, medium and high based on their overall perception scores. The distribution across the three districts is presented in Table 6.

Table 6.

Distribution of Tribal Respondents According to their Overall Perception of the Role Performance of Economic Institutions.

S. No.	Category	Salem (n = 90)		Tiruvannamalai (n = 90)		Viluppuram (n = 90)		Total (n = 270)
S. No.	Category	No.	%	No.	%	No.	%	No.	%
1	Low	21	23.33	22	24.44	19	21.11	62	22.96
2	Medium	33	36.67	39	43.33	36	40.00	108	40.00
3	High	36	40.00	29	32.22	35	38.89	100	37.04
Total		90	100.00	90	100.00	90	100.00	270	100.00
Mean		34.789		34.422		34.933		34.715
ANOVA		F-value: 0.208^NS				P value: .813

Source: Field Survey (2021).

Note: ANOVA, analysis of variance; NS, not significant.

Examining the overall perception of tribal respondents reveals that two-fifths (40.00%) of tribal respondents had a medium perception level, followed by 37.04 per cent with a high perception, and 22.96 per cent with a low perception regarding the role performance of economic institutions in tribal society.

The one-way analysis of variance (ANOVA) result (F-value: 0.208, P value: .813) indicates no statistically significant difference in perceptions among the three districts. In Salem district, 40.00 per cent exhibited a high level of perception, followed by medium perception (36.67%) and low perception (23.33%). Tiruvannamalai district saw slightly over two-fifths (43.33%) with medium perception, followed by high perception (32.22%) and low perception (24.44%). Viluppuram district had 40.00 per cent with a medium perception, followed by high perception (38.89%) and low perception (21.11%). The ANOVA results imply that the factors influencing perception are consistent across the districts; however, the district-wise breakdowns suggest subtle variations in the perception levels.

Moving beyond district-wise breakdowns, the broader analysis of overall perception unveils a predominant medium to a high level of perception regarding the role performance of economic institutions. The prevalent medium to high overall perception underscores a foundational trust in these institutions, particularly rooted in tangible benefits observed in agriculture. Cooperative societies play a crucial role, significantly contributing to farming activities and facilitating access to credit. The widespread acknowledgement of LAMPS involvement in interest-free crop loans, provision of inputs, marketing facilities and employment opportunities aligns seamlessly with this positive perception, underscoring the visible impact on livelihoods.

Additionally, the positive perception reflects successful financial inclusion initiatives, including microcredit promotion through SHGs. Commercial banks positively influence tribal communities by actively participating in SHGs, mobilising savings and empowering tribal women through improved financial literacy. Tribal respondents value nationalised banks for aiding through SHGs and reducing dependence on local moneylenders. This underscores the broader significance of economic institutions in enhancing the socio-economic status of tribal communities.

While a substantial portion demonstrated a medium to high level of perception, the 22.96 per cent with a low perception level raises important considerations. The individual statement-level analysis also uncovers specific areas of concern, such as challenges in entrepreneurship empowerment, limited access to financial services and obstacles in fully utilising cooperative functions. The complexities around aligning financial services with cultural values, accessibility, knowledge gaps and illiteracy are crucial factors affecting the perceptions of tribal respondents.

The favourable overall perception observed among tribal respondents extends beyond mere economic well-being, encompassing a broader spectrum that aligns with the SDGs of the United Nations. However, the findings also indicate the necessity for targeted interventions and strategic actions to address identified challenges, emphasising the ongoing need for efforts to enhance financial inclusion, community empowerment and sustainable development within tribal communities.

To this end, focused initiatives should aim at improving financial literacy, bridging knowledge gaps and promoting education to empower individuals to make well-informed financial decisions. Culturally aligned programmes specifically addressing entrepreneurship and economic empowerment need to be developed, while prioritising accessibility to financial services, particularly in remote areas, is paramount. By implementing coordinated actions that address both overarching and localised challenges, we can ensure that the positive perceptions observed continue to evolve, ultimately fostering holistic empowerment within tribal societies and contributing significantly to the achievement of the SDGs.

Policy Recommendations

Building on positive overall perceptions and identified needs, the following policy recommendations aim to enhance economic institution access and efficiency within tribal societies, considering unique social, cultural and geographical challenges.

Mobile banking outreach: Implement SMS-based mobile banking programmes to overcome geographical barriers, providing financial services and education directly to tribal members. Collaborate with network providers for reliable connectivity and offer user-friendly services for less-educated tribal communities.

Community-based financial literacy initiatives: Establish community-based financial literacy programmes collaboratively with local leaders and educators. These initiatives should create culturally sensitive and language-appropriate modules, empowering tribal individuals with the knowledge needed for informed financial decisions.

Promotion of cooperative microfinance groups: Broaden the impact of microfinance initiatives by promoting and strengthening cooperative microfinance groups that include both men and women in tribal communities. Despite challenges posed by the lack of land ownership, extending financial services through inclusive microfinance groups become crucial. Provide comprehensive training to empower all tribal members in managing these cooperatives effectively.

Tailored loan products for tribal entrepreneurs: Collaborate between economic institutions and entrepreneurship agencies to build confidence in offering tribal-specific entrepreneurship loans. Ensure specialised loan products accommodate the cyclical nature of tribal economies, with flexible repayment options aligned with cultural and seasonal aspects of tribal livelihoods. Mandate beneficiaries’ engagement with entrepreneurship development agencies for comprehensive training, supporting the success and sustainability of their businesses.

Inclusive financial planning workshops: Organise workshops in collaboration with economic institutions, NGOs and local organisations to cater to the specific economic goals and aspirations of tribal communities, addressing knowledge gaps and empowering tribal communities in effective financial resource management.

Enhancing employment opportunities: Implement policies for targeted employment creation within tribal societies, incorporating skill development programmes, vocational training and collaboration with industries for sustainable employment avenues. Additionally, leverages the role of banks in promoting tribal entrepreneurship, creating associated employment opportunities. Emphasise the pivotal role of LAMPS in forest product collection and marketing, contributing further to employment generation within tribal communities.

Incorporating these recommendations ensures a comprehensive approach to address the challenges faced by tribal societies, contributing to the ongoing discourse on improving economic institution access and efficiency within tribal societies, with broader goals of sustainable development and empowerment.

Conclusion

According to the findings of this study, economic institutions play a crucial role in determining and enhancing the livelihoods of tribal communities by providing financial support and essential services. This assertion emphasises a potential convergence between the SDGs and the functions of economic institutions, notably in terms of poverty reduction, promoting education and fostering social and financial inclusion within STs. The established scale and the results serve as a platform for future research on the functions of economic institutions and as an important tool for comprehending their complex operations.

The examination of results unveils a nuanced understanding of economic institutions. The positive outlook on economic institutions reflects a foundational trust in economic institutions, particularly in the realm of agriculture. The study highlights the intricate nature of economic institutions in tribal contexts, positioning commercial banks as agents of change. Beyond financial services, they play a pivotal role in liberating tribes from local moneylenders, facilitating a significant stride toward financial independence within the tribal landscape. In the realm of women’s financial empowerment, commercial banks play a crucial role in navigating the complex interplay of tribal aspirations, cultural values and communal interests to reshape gender dynamics and promote inclusivity.

While the commendable reduction in reliance on informal lenders is observed, challenges persist in swiftly addressing urgent financial needs due to the difficulty formal institutions face in providing quick loans. This complexity in the financial landscape is influenced by factors such as geographic isolation, accessibility restrictions, ignorance and low literacy rates. Recognising these challenges, targeted interventions are imperative, necessitating careful consideration and alignment with the unique values and needs of tribal communities to foster effective financial empowerment and entrepreneurship.

Moving forward, the policy recommendations outlined in this study provide strategic insights for improving the access and efficiency of economic institutions within tribal societies. These recommendations address specific areas identified in the study, ensuring a holistic approach to foster sustainable development and empowerment. Mobile banking outreach programmes, community-based financial literacy initiatives, promotion of cooperative microfinance groups, tailored loan products for tribal entrepreneurs and inclusive financial planning workshops are proposed as key initiatives. These recommendations aim to overcome geographical barriers, align financial services with cultural values and promote inclusive economic growth within tribal communities.

In conclusion, this study highlights the complex interactions between tribal populations and economic institutions, illuminating their roles, functions and perceptions. Even while commercial banks and cooperative societies have displayed positive influences in various areas, disparities and challenges persist. These insights must be used by policymakers, stakeholders and researchers to build focused efforts that put financial inclusion, sustainable development and the unique aspirations of tribal people at the forefront. By aligning economic institution roles with the values and needs of tribal communities, we can collectively strive towards a future that empowers, uplifts and ensures the well-being of all.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors declared that the research is funded by the University Grand Commission (UGC), New Delhi, India under the National Fellowship for Other Background Classes (NF-OBC), however, no financial support was received for the authorship and/or publication of this article.

ORCID iD

A. Prasanth

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